Heretofore considerable work has been done on night vision devices which collect energy from scenes in multiple bands and convert the energy to electrical signals which are digitally processed, fused and presented in real time as full motion video on a display for viewing by the user. One of these systems is a so-called two color system in which infrared images and visible light images are fused together in the final image. These prior multiband digitally processed fusion techniques are intended to increase image detail. A need still exists, however, for a way to blend co-registered low visible light level images with thermal infrared (IR) images in a way that maximizes the scene detail, especially in very low light conditions, in scenes with very bright lights, and in smoke or fog conditions.
Specifically, in the past, infrared light and visible light have been fused together in a two color image fusion process that blends co-registered low light level images. In these systems increased contrast enhancement is available through a thermal local area contrast enhancement (LACE) algorithm, and is especially useful in low light and in well illuminated scenarios. Like techniques are applied in the visible light channel. Both of these local area contrast enhancement (LACE) techniques involved histogram preprocessor functions to add contrast for improved detail. Moreover, a number of noise rejection functions and algorithms were used to correct for nonuniformity related to temperature changes and shifts. Additionally, gain correction algorithms provided uniformity for each pixel, whereas row noise reduction algorithms normalized the levels of the rows. Further, cluster de-noise algorithms removed flashing out of a family of pixels in low light scenarios, whereas optical distortion correction was applied between the co-registered visible light images and the IR images using translation, rotation and magnification. Finally, focal actuated vergence algorithms were utilized to correct for parallax errors.
All of the above techniques were used to remove noise and other artifacts prior to being passed to a fusion algorithm to provide a co-registered fused image composed of infrared and visible light images.
However, there is a need for further improvement of the fused image to be able to emphasize structural content information in the final fused image, thus to further improve image detail.